HackerPapers

arXiv:2308.06403cs.CY

Taboo and Collaborative Knowledge Production: Evidence from Wikipedia

Kaylea Champion, Benjamin Mako Hill

HN submission. Found in a submission link or body. Submitters do not count as commenters in the main ranking; a submission is not an endorsement.

Abstract

By definition, people are reticent or even unwilling to talk about taboo subjects. Because subjects like sexuality, health, and violence are taboo in most cultures, important information on each of these subjects can be difficult to obtain. Are peer produced knowledge bases like Wikipedia a promising approach for providing people with information on taboo subjects? With its reliance on volunteers who might also be averse to taboo, can the peer production model produce high-quality information on taboo subjects? In this paper, we seek to understand the role of taboo in knowledge bases produced by volunteers. We do so by developing a novel computational approach to identify taboo subjects and by using this method to identify a set of articles on taboo subjects in English Wikipedia. We find that articles on taboo subjects are more popular than non-taboo articles and that they are frequently vandalized. Despite frequent vandalism attacks, we also find that taboo articles are higher quality than non-taboo articles. We hypothesize that stigmatizing societal attitudes will lead contributors to taboo subjects to seek to be less identifiable. Although our results are consistent with this proposal in several ways, we surprisingly find that contributors make themselves more identifiable in others.

arXiv comments
Journal reference
Proceedings of the ACM on Human-Computer Interaction 7 (CSCW2): 299:1-299:25 (2023)
DOI
doi:10.1145/3610090
Subjects
cs.CYComputers and Society cs.HCHuman-Computer Interaction

On Hacker News

No comments linking this paper were found in the collected sources. Found in 1 HN submission from Aug 2023 to Aug 2023. Open submission discussions.

Comments linking this paper, per year.

Discussed in comments0 threads

No comments linking this paper were found in the collected sources. Open submission discussions.

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.